Dissolution Kinetics of Different Inorganic Oilfield Scales in Green Formulations

Abstract

Scale mineral deposition is a critical problem that hinders the daily production of oil and gas fields. Chemical removal of these scales, based on the scale type, is common. In this paper, borax and diethylene tremaine penta acetic (DTPA) acid-based formulations are used for the removal of sulfides, carbonates, and sulfate scales. In particular, the dissolution rates of sulfide (pyrite, pyrrhotite, and galena), sulfate (celestite and barite), and carbonate (calcite) scales were investigated in a rotating disc apparatus at typical well conditions. Scanning electron microscopy–energy-dispersive X-ray and X-ray diffraction analyses were performed for characterizing scale composition and type. The effect of temperature, scale type, and formulation on the dissolution rate is studied. Even though borax formulation has been developed for the sulfide scale removal, it showed a high dissolution rate for the carbonate scale (7.23 × 10–7 mol·L–1·s–1·cm–2). For the sulfide scale, the highest dissolution in borax formulation was obtained with galena (lead sulfide, PbS), followed by pyrrhotite, and the lowest dissolution was reported for pyrite (1.55 × 10–8 mol·L–1·s–1·cm–2). Borax formulation was found to be inefficient in the removal of sulfate scales with a dissolution rate lower than carbonate and sulfide scales by 3 and 2 orders of magnitude, respectively. Similarly, DTPA-based formulation has yielded the highest dissolution for the carbonate scale (7.98 × 10–6 mol·L–1·s–1·cm–2). However, for sulfate, DTPA-based formulation showed better performance than borax. The increase in temperature leads to an increase in the dissolution rate for almost all types of scales; however, DTPA-based formulation showed improved performance with temperature. Both formulations are efficient in removing sulfate- and sulfide-rich scales. The experimental results of DTPA have been validated by density functional theory calculations of binding energies between DTPA and metal ions present in the mixed scale.

Development of Artificial Neural Network Models for the Simulation of a CaCO3 Scale Formation Process in the Presence of Monoethylene Glycol (MEG) in Dynamic Tube Blocking Test Equipment

“…The second database consisted of six experiments, totaling 7705 data points. Those experiments were conducted with fixed values of pressure, temperature, C HCO 3 − and C Ca 2+ , and varying C MEG (10,20,30,50,60, and 70 v/v %). This database was used to separately validate the models constructed by the ANN for each experiment.…”

“…Gas hydrate originates from the crystallization of water molecules encapsulating small and light gas molecules (e.g., CO 2 , methane, and propane) under operating conditions with high pressure and low temperature, such as those found in deep and ultradeep water. , The most practical and economical method for preventing hydrate formation or others kinds of obstructions in lines (e.g., scales) is using chemical inhibitors. − Thermodynamic hydrate inhibitors (THIs) are typically injected into the production line to prevent the formation of gas hydrates. THIs consist of alcohols or glycols, such as methanol, triethylene glycol (TEG), and monoethylene glycol (MEG), and function by moving the equilibrium curve envelope toward lower temperature and higher pressure. , …”

Development of Artificial Intelligence Models Applied to the Flow Assurance Problems in the Oil and Gas Industry

“… Develop the classificatory models for the pH class (2,3,4,5,6,7,8,9,10);  Develop the prediction models for the pH values in the range 2-10;…”

“…Podendo ser aplicados no monitoramento de sistemas como Sistema Gerador de Nitrogênio, utilizado para remediar alguns problemas de incrustação, dado que sua cinética depende fortemente do pH do sistema. Foram criados modelos de classificação para o pH do sistema (2,3,4,5,6,7,8,9,10) usando Redes Neurais Convolucionais (CNN), Máquina de Vetor de Suporte e Árvores de Decisão.…”